1. Field of the Invention
The present disclosure relates generally to an electronic device and an eye region detecting method.
2. Description of Related Art
Recently, technologies based on biometrics have been widely applied to electronic devices. The biometric technology is a technology that measures physical and behavioral characteristics of humans through an automated device, and utilizes the measured data for personal identification. The biometric technology may recognize physical characteristics, for example, a fingerprint, a palm print, a face, the shape of a hand, an iris, a vein, and the like, so as to utilize the recognized data as a means of personal identification.
The iris recognition of the biometric technology is a technology that recognizes an iris that has a unique pattern for each person. The iris of a person has features that do not change over the course of their life and is unique to that person, and, thus, iris recognition is an actively conducted biometric technology. Also, the iris recognition has a faster processing rate and a higher reliability and recognition rate than other biometric technologies and, thus, may be acknowledged as an important branch of biometric technology.
In order to apply iris recognition to a portable electronic device such as a mobile phone and the like, there is a need for a technology which can detect an eye region from a high-definition facial image in real time.
However, the conventional method of detecting the eye region from the high-definition facial image in real-time, requires the use of expensive equipment and it is further inconvenient to obtain an image. As a result, the technology has not been widely utilized for portable electronic devices but has been frequently used for a field that requires security.
Examples of the conventional eye region detection technologies include an eye region detection technology using the AdaBoost algorithm, a rapid eye detection that uses the brightness of an eye region and the surrounding region, and the like. However, the conventional eye region detection technologies require a great amount of algorithm operation and thus, have difficulty in detecting an eye from a high-definition facial image in a mobile environment in real time.